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In this work, we propose a robust iris segmentation method for non-ideal ocular images, referred to as Polar Spline RANSAC, which approximates the iris shape as a closed curve with arbitrary degrees of freedom. The method is robust to several nonidealities, such as poor contrast, occlusions, gaze deviations, pupil dilation, motion blur, poor focus, frame interlacing, differences in image resolution, specular reflections, and shadows. Unlike most techniques in the literature, the proposed method obtains good performance in harsh conditions with different imaging wavelengths and datasets. We also investigate the role of different illumination compensation techniques on the iris segmentation process. The experiments showed that the proposed method results in higher or comparable accuracy with respect to other competing techniques presented in the literature for images acquired in non-ideal conditions. Furthermore, the proposed segmentation method is generalizable and can achieve competitive performance with different state-of-the-art feature extraction and matching techniques. In particular, in conjunction with a well-known recognition schema, it achieved Equal Error Rate of 4.34% on DB WVU, Equal Error Rate of 5.98% on DB QFIRE, and pixel-wise classification error rate of 0.0165 on DB UBIRIS v2. Moreover, experiments using different illumination compensation techniques demonstrate that algorithms based on the Retinex model offer improved segmentation and recognition accuracy, thereby highlighting the importance of adopting illumination models for processing non-ideal ocular images. • A robust iris segmentation method for non-ideal ocular images (Polar Spline RANSAC). • Extensive study on illumination compensation techniques for iris segmentation. • Good performance in unfavorable conditions for different wavelengths and datasets. [ABSTRACT FROM AUTHOR]

Pregestational Diabetes Mellitus (PDM) during pregnancy constitutes an unfavorable embryonic and fetal development environment, with a high incidence of congenital malformations (CM). Neural tube defects are the second most common type of CM in children of diabetic mothers (CDM), who also have an elevated risk of developing neurodevelopmental disorders. The mechanisms that lead to these neuronal disorders in CDM are not yet fully understood. The present study aimed to know the effect of hyperglycemia on proliferation, neuronal differentiation percentage, and expression of neuronal differentiation mRNA markers in human umbilical cord Wharton's jelly mesenchymal stem cells (hUCWJMSC) of children from normoglycemic pregnancies (NGP) and PDM. We isolated and characterized hUCWJMSC by flow cytometry, immunofluorescence, RT-PCR and were induced to differentiate into adipocytes, osteocytes, and neurons. Proliferation assays were performed to determine the doubling time, and Nestin, TUBB3, FOXO1, KCNK2, LMO3, and MAP2 mRNA gene expression was assessed by semiquantitative RT-PCR. Hyperglycemia significantly decreased proliferation and neuronal differentiation percentage in NGP and PDM cells treated with 40 mM d -glucose. Nestin mRNA expression decreased under control glycemic conditions, while FOXO1, KCNK2, LMO3, and MAP2 mRNA expression increased during neuronal differentiation in both NGP and PDM cells. On the other hand, under hyperglycemic conditions, Nestin was significantly decreased in cells from NGP but not in cells from PDM, while mRNA expression of FOXO1 and LMO3 was significantly increased in cells from NGP, but not in cells from PDM. We found evidence that maternal PDM, with hyperglycemia in culture, affects the biological properties of fetal cells. All these results could be part of fetal programming. • Diabetic pregnancy and hyperglycemia differentially reduce neuronal differentiation. • Diabetic pregnancy and hyperglycemia differentially regulate Nestin mRNA expression. • Diabetic pregnancy and hyperglycemia differentially regulate FOXO1 mRNA expression. • Diabetic pregnancy and hyperglycemia differentially regulate LMO3 mRNA expression. • Neuronal differentiation of MSC could serve as an indicator of hyperglycemia effects. [ABSTRACT FROM AUTHOR]

Abstract Diabetes in pregnancy constitutes an unfavorable environment for embryonic and fetal development, where the child has a higher risk of perinatal morbidity and mortality, with high incidence of congenital malformations and predisposition to long-term metabolic diseases that increase with a hypercaloric diet. To analyze whether hyperglycemia differentially affects proliferation, apoptosis, and mRNA expression in cells from children of normoglycemic pregnancies (NGPs) and diabetes mellitus pregnancies (DMPs), we used umbilical cord Wharton jelly cells as a research model. Proliferation assays were performed to analyze growth and determine the doubling time, and the rate of apoptosis was determined by flow cytometry-annexin-V assays. AMPK, BNIP3, HIF1α, and p53 mRNA gene expression was assessed by semi-quantitative RT-PCR. We found that hyperglycemia decreased proliferation in a statistically significant manner in NGP cells treated with 40 mM D-glucose and in DMP cells treated with 30 and 40 mM D-glucose. Apoptosis increased in hyperglycemic conditions in NGP and DMP cells. mRNA expression of BNIP3 and p53 was significantly increased in cells from DMPs but not in cells from NGPs. We found evidence that maternal irregular metabolic conditions, like diabetes with hyperglycemia in culture, affect biological properties of fetal cells. These observations could be a constituent of fetal programming. Highlights • Hyperglycemia differentially affects proliferation of cells from diabetic pregnancies. • Diabetic pregnancy and hyperglycemia differentially regulate BNIP3 mRNA expression. • Pregnancy in diabetics and hyperglycemia differentially regulate p53 mRNA expression. [ABSTRACT FROM AUTHOR]